The Consequences of Predicting Scientific Impact in Psychology Using Journal Impact Factors

摘要

An academic journal's impact factor (hereafter JIF) is an average measure of the citation count of individual articles published inthat journal. JIF is used to assess merit, predict impact, and allocate resources, but the actual number of citations to individualarticles is only modestly correlated with the JIFs of the journals in which they are published.We counted Psycinfo citations to1,133 articles published in nine leading psychology journals (1996-2005). Both article length (r =.31) and reference list length(r = .41) predicted log-transformed citation counts better than JIF (r = .27). Articles with fewer graphs and more structuralequation models were more frequently cited. Citation count was better predicted by a model based on article length andcitation count rather than JIF. When JIF was used to predict citation count, the impact of women authors and social scienceresearch was underestimated.These findings distinguish impact in science, as measured by JIF, from actual impact in psychology,and they show the unintended consequences of using a measure of the former to predict the latter.